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Electronic Tongues, Electronic Noses and Other Chemometric-Based Approaches for Analytical Applications

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Chemical Sensors".

Deadline for manuscript submissions: closed (15 June 2023) | Viewed by 7356

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Special Issue Editors

Prof. Dr. Manel Del Valle

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Sensors & Biosensors Group, Department of Chemistry, Universitat Autònoma de Barcelona, Edifici Cn, Campus de Bellaterra (Cerdanyola del Vallés), 08193 Barcelona, Spain
Interests: automation in analytical chemistry; bioinspired analytical systems; FIA systems; SIA systems; chemical sensors; biosensors; genosensors; aptamer sensors; electrochemical impedance spectroscopy; multisensor systems; electronic tongues
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Dr. Xavier Cetó

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Guest Editor

Department of Chemistry, Faculty of Sciences, Universitat Autònoma de Barcelona 08193 Bellaterra, Barcelona, Spain
Interests: electrochemical (bio)sensors; screen-printed devices; electronic tongues; chemometrics; food authentication
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Over the last few years, there has been an increasing demand for fast, highly sensitive and selective methods of analysis to meet new challenges in environmental monitoring, food safety and public health. In response to this demand, chemo- and bio-sensors have arisen as promising tools, which offer accurate chemical data in a timely and cost-effective manner. However, the difﬁculty to obtain sensors with appropriate selectivity and sensitivity for a given analyte, and to solve analytical problems which do not require the quantiﬁcation of a certain analyte, but an overall effect on a biological system (e.g. toxicity, quality indices, provenance, freshness, etc.), led to the concept of electronic noses (ENs) and electronic tongues (ETs) as a new strategy to tackle these problems.

These analytical systems are inspired by the sensory ability of taste in mammals, where a few receptors can respond in a distinct way to a large variety of substances. This principle is then coupled with a complex data treatment stage analogous to the brain functioning, which allows us to quantify or classify a large amount of analytes. These biomimetic systems, unlike conventional approaches, are directed towards the combination of low selectivity sensor arrays, which may show cross-response features, to obtain added value in the generation of the analytical information.

In this context, this Special Issue aims to cover the advances of such biomimetic sensing systems, by creating a collection of papers dealing with the use of multivariate data analysis methods (even not based on sensors, but which methodologies are suitable for those), novel applications and strategies for multicomponent analysis using single sensors or sensor arrays and any other related biologically inspired sensing approach. Both research papers and review articles will be considered. We look forward to and welcome your participation in this Special Issue.

Topics of interest include, but are not limited to, the following:

New sensing and biosensing technologies for developing electronic nose and electronic tongue analysis systems;
Applications in identification / quantification of compounds with sensor array principles;
Use of novel data treatment approaches in electronic nose / electronic tongue methodology;
Study of key issues on long-term usage of these systems: calibration transfer, correction of drifts, sensor replacement.

Prof. Dr. Manel Del Valle
Dr. Xavier Cetó
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

Electronic tongues
Electronic noses
Electronic eyes
Taste sensor
Sensors and biosensors arrays
Sensors networks
Hybrid systems
Chemometrics
Multivariate data analysis
Pattern recognition
Principal component analysis (PCA)
Partial least squares regression (PLS)
Artificial neural networds (ANNs)
Support vector machines (SVMs)
Agri-food analysis
Environmental analysis
Biomedical applications

Published Papers (3 papers)

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Research

9 pages, 2739 KiB

Open AccessCommunication

Identification of the Principle of Taste Sensors to Detect Non-Charged Bitter Substances by ¹H-NMR Measurement

by Misaki Ishida, Haruna Ide, Keishiro Arima, Zeyu Zhao, Toshiro Matsui and Kiyoshi Toko

Sensors 2022, 22(7), 2592; https://doi.org/10.3390/s22072592 - 28 Mar 2022

Cited by 6 | Viewed by 2140

Abstract

A taste sensor with lipid/polymer membranes is attracting attention as a method to evaluate taste objectively. However, due to the characteristic of detecting taste by changes in membrane potential, taste sensors cannot measure non-charged bitter substances. Many foods and medicines contain non-charged bitter substances, and it is necessary to quantify these tastes with sensors. Therefore, we have been developing taste sensors to detect bitter tastes caused by non-charged substances such as caffeine. In previous studies, a sensor for detecting bitterness caused by caffeine and theobromine, theophylline, was developed, using a membrane modified with hydroxybenzoic acid (HBA) as the sensing part. The sensor was designed to form intramolecular hydrogen bonds (H-bonds) between the hydroxy group and carboxy group of HBA and to successively cause the intermolecular H-bonds between HBA and caffeine molecules to be measured. However, whether this sensing principle is correct or not cannot be confirmed from the results of taste sensor measurements. Therefore, in this study, we explored the interaction between HBA and caffeine by ¹H-nuclear magnetic resonance spectroscopy (NMR). By the ¹H NMR detection, we confirmed that both the substances interact with each other. Furthermore, the nuclear Overhauser effect (NOE) of intermolecular spatial conformation in solution was measured, by which 2,6-dihydroxybenzoic acid (2,6-DHBA) preferably interacted with caffeine via the H-bonding and stacking configuration between aromatic rings. Identifying the binding form of 2,6-DHBA to caffeine was estimated to predict how the two substances interact. Full article

(This article belongs to the Special Issue Electronic Tongues, Electronic Noses and Other Chemometric-Based Approaches for Analytical Applications)

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13 pages, 3134 KiB

Open AccessArticle

Carbon SH-SAW-Based Electronic Nose to Discriminate and Classify Sub-ppm NO₂

by Carlos Cruz, Daniel Matatagui, Cristina Ramírez, Isidro Badillo-Ramirez, Emmanuel de la O-Cuevas, José M. Saniger and Mari Carmen Horrillo

Sensors 2022, 22(3), 1261; https://doi.org/10.3390/s22031261 - 07 Feb 2022

Cited by 9 | Viewed by 2277

Abstract

In this research, a compact electronic nose (e-nose) based on a shear horizontal surface acoustic wave (SH-SAW) sensor array is proposed for the NO₂ detection, classification and discrimination among some of the most relevant surrounding toxic chemicals, such as carbon monoxide (CO), ammonia (NH₃), benzene (C₆H₆) and acetone (C₃H₆O). Carbon-based nanostructured materials (CBNm), such as mesoporous carbon (MC), reduced graphene oxide (rGO), graphene oxide (GO) and polydopamine/reduced graphene oxide (PDA/rGO) are deposited as a sensitive layer with controlled spray and Langmuir–Blodgett techniques. We show the potential of the mass loading and elastic effects of the CBNm to enhance the detection, the classification and the discrimination of NO₂ among different gases by using Machine Learning (ML) techniques (e.g., PCA, LDA and KNN). The small dimensions and low cost make this analytical system a promising candidate for the on-site discrimination of sub-ppm NO₂. Full article

(This article belongs to the Special Issue Electronic Tongues, Electronic Noses and Other Chemometric-Based Approaches for Analytical Applications)

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Graphical abstract

14 pages, 3828 KiB

Open AccessArticle

Electrical Properties of Two Types of Membrane Component Used in Taste Sensors

by Zhanyi Xiang, Yifei Jing, Hidekazu Ikezaki and Kiyoshi Toko

Sensors 2021, 21(24), 8343; https://doi.org/10.3390/s21248343 - 14 Dec 2021

Cited by 6 | Viewed by 2189

Abstract

The lipid phosphoric acid di-n-decyl ester (PADE) has played an important role in the development of taste sensors. As previously reported, however, the concentration of PADE and pH of the solution affected the dissociation of

H^{+}

, which made the measurement results [...] Read more.

H^{+}

, which made the measurement results less accurate and stable. In addition, PADE caused deterioration in the response to bitterness because PADE created the acidic environment in the membrane. To solve these problems, our past study tried to replace the PADE with a completely dissociated substance called tetrakis [3,5-bis (trifluoromethyl) phenyl] borate sodium salt dehydrate (TFPB) as lipid. To find out whether the two substances can be effectively replaced, it is necessary to perform an in-depth study on the properties of the two membranes themselves. In this study, we fabricated two types of membrane electrodes, based on PADE or TFPB, respectively, using 2-nitrophenyl octyl ether (NPOE) as a plasticizer. We measured the selectivity to cations such as

{Cs}^{+}

K^{+}

{Na}^{+}

and

{Li}^{+}

, and also the membrane impedance of the membranes comprising PADE or TFPB of the different concentrations. As a result, we found that any concentration of PADE membranes always had low ion selectivity, while the ion selectivity of TFPB membranes was concentration-dependent, showing increasing ion selectivity with the TFPB concentrations. The ion selectivity order was

{Cs}^{+} > K^{+} > {Na}^{+} > {Li}^{+}

. The hydration of ions was considered to participate in this phenomenon. In addition, the membrane impedance decreased with increasing PADE and TFPB concentrations, while the magnitudes differed, implying that there is a difference in the dissociation of the two substances. The obtained results will contribute to the development of novel receptive membranes of taste sensors. Full article

(This article belongs to the Special Issue Electronic Tongues, Electronic Noses and Other Chemometric-Based Approaches for Analytical Applications)

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